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2020 – today
- 2023
[c13]Sajal Dash, Mohammad Alaul Haque Monil, Junqi Yin, Ramu Anandakrishnan, Feiyi Wang:
Distributing Simplex-Shaped Nested for-Loops to Identify Carcinogenic Gene Combinations. IPDPS 2023: 974-984- [c12]Aristeidis Tsaris
, Joshua Romero, Thorsten Kurth, Jacob D. Hinkle, Hong-Jun Yoon, Feiyi Wang, Sajal Dash, Georgia D. Tourassi:
Scaling Resolution of Gigapixel Whole Slide Images Using Spatial Decomposition on Convolutional Neural Networks. PASC 2023: 2:1-2:11 - 2022
- [c11]Folami Alamudun, Jacob D. Hinkle, Sajal Dash, Benjamín Hernández, Aristeidis Tsaris, Hong-Jun Yoon:
Distilling Knowledge from Ensembles of Cluster-Constrained-Attention Multiple-Instance Learners for Whole Slide Image Classification. IEEE Big Data 2022: 3393-3397 - [c10]Awais Khan, Arnab K. Paul, Christopher Zimmer, Sarp Oral, Sajal Dash, Scott Atchley, Feiyi Wang:
Hvac: Removing I/O Bottleneck for Large-Scale Deep Learning Applications. CLUSTER 2022: 324-335 - [c9]Sajal Dash, Benjamín Hernández, Aristeidis Tsaris, Folami T. Alamudun, Hong-Jun Yoon, Feiyi Wang:
A Scalable Pipeline for Gigapixel Whole Slide Imaging Analysis on Leadership Class HPC Systems. IPDPS Workshops 2022: 1266-1274 - [c8]Junqi Yin, Guannan Zhang, Huibo Cao, Sajal Dash, Bryan C. Chakoumakos, Feiyi Wang:
Toward an Autonomous Workflow for Single Crystal Neutron Diffraction. SMC 2022: 244-256 - 2021
- [c7]Sajal Dash, Qais Al-Hajri, Wu-chun Feng, Harold R. Garner, Ramu Anandakrishnan:
Scaling Out a Combinatorial Algorithm for Discovering Carcinogenic Gene Combinations to Thousands of GPUs. IPDPS 2021: 837-846 - [c6]Sajal Dash, Junqi Yin, Mallikarjun Shankar, Feiyi Wang, Wu-chun Feng:
Mitigating Catastrophic Forgetting in Deep Learning in a Streaming Setting Using Historical Summary. DRBSD@SC 2021: 11-18 - [c5]Pravallika Devineni, Panchapakesan Ganesh, Nikhil Sivadas, Abhijeet Dhakane, Ketan Maheshwari, Drahomira Herrmannova, Ramakrishnan Kannan, Seung-Hwan Lim, Thomas E. Potok, Jordan B. Chipka, Priyantha Mudalige, Mark Coletti, Sajal Dash, Arnab Kumar Paul, Sarp Oral, Feiyi Wang, Bill Kay, Melissa R. Allen-Dumas, Christa Brelsford, Joshua R. New, Andy Berres, Kuldeep R. Kurte, Jibonananda Sanyal, Levi Sweet, Chathika Gunaratne, Maxim A. Ziatdinov, Rama K. Vasudevan, Sergei V. Kalinin, Olivera Kotevska, Jean C. Bilheux, Hassina Z. Bilheux, Garrett E. Granroth, Thomas Proffen, Rick Riedel, Peter F. Peterson, Shruti R. Kulkarni, Kyle P. Kelley, Stephen Jesse, Maryam Parsa:
Smoky Mountain Data Challenge 2021: An Open Call to Solve Scientific Data Challenges Using Advanced Data Analytics and Edge Computing. SMC 2021: 361-382 - 2020
- [c4]Sajal Dash, Archi Dasgupta:
Towards a Universal Classifier for Crystallographic Space Groups: A Trickle-Down Approach to Handle Data Imbalance. SMC 2020: 465-478
2010 – 2019
- 2019
- [c3]Junqi Yin, Shubhankar Gahlot, Nouamane Laanait, Ketan Maheshwari, Jack Morrison, Sajal Dash, Mallikarjun Shankar:
Strategies to Deploy and Scale Deep Learning on the Summit Supercomputer. DLS@SC 2019: 84-94 - 2017
- [c2]Sajal Dash, Anshuman Verma, Chris North, Wu-chun Feng:
Portable Parallel Design of Weighted Multi-Dimensional Scaling for Real-Time Data Analysis. HPCC/SmartCity/DSS 2017: 10-17 - 2011
- [c1]Sajal Dash, Jack Snoeyink:
On the energy of bifurcated hydrogen bonds for protein structure prediction. BIBM Workshops 2011: 334-337
Coauthor Index
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last updated on 2023-09-08 10:06 CEST by the dblp team
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